code: def check_missing_values(
      data: pd.DataFrame,
      column_name: str,
      split: Optional[str] = "",
  ):
      num_missing_values = data[column_name].isnull().sum()
      if num_missing_values > 0:
          raise ValueError(
              f"Label column '{column_name}' contains missing values in the "
              f"{split} dataframe. You may want to filter your data because "
              "missing label is currently not supported."
          )
  
imports: import collections
  import json
  import logging
  import warnings
  from io import BytesIO
  from typing import Dict, List, Optional, Tuple, Union
  import pandas
  import PIL
  import pytesseract
  from autogluon.core.utils import infer_problem_type
  from ..constants import BINARY, CATEGORICAL, CLASSIFICATION, DOCUMENT_IMAGE, DOCUMENT_PDF, IDENTIFIER, IMAGE, IMAGE_BYTEARRAY, IMAGE_PATH, MULTICLASS, NER, NER_ANNOTATION, NULL, NUMERICAL, OBJECT_DETECTION, OPEN_VOCABULARY_OBJECT_DETECTION, REGRESSION, ROIS, SEMANTIC_SEGMENTATION, SEMANTIC_SEGMENTATION_GT, SEMANTIC_SEGMENTATION_IMG, TEXT, TEXT_NER
  from .utils import is_rois_input
label_desc: Use image node_id 11 for calling a global function with example usage: check_missing_values(data, column_name, split) without return types